Sheu, K. M. | Search bioRxiv

bioRxiv2020

NFκB dynamics determine stimulus-responsive epigenomic reprogramming in macrophages

The epigenome defines the cell type, but also shows plasticity that enables cells to tune their gene expression potential to the context of extracellular cues. This is evident in immune sentinel cells such as macrophages, which can respond to pathogens and cytokines with phenotypic shifts that are driven by epigenomic reprogramming1. Recent studies indicate that this reprogramming arises from the activity of transcription factors such as nuclear factor kappa-light-chain-enhancer of activated B cells (NF{kappa}B), which binds not only to available enhancers but may produce de novo enhancers in previously silent areas of the genome2. Here, we show that NF{kappa}B reprograms the macrophage epigenome in a stimulus-specific manner, in response only to a subset of pathogen-derived stimuli. The basis for these surprising differences lies in the stimulus-specific temporal dynamics of NF{kappa}B activity. Testing predictions of a mathematical model of nucleosome interactions, we demonstrate through live cell imaging and genetic perturbations that NF{kappa}B promotes open chromatin and formation of de novo enhancers most strongly when its activity is non-oscillatory. These de novo enhancers result in the activation of additional response genes. Our study demonstrates that the temporal dynamics of NF{kappa}B activity, which encode ligand identity3, can be decoded by the epigenome through de novo enhancer formation. We propose a mechanistic paradigm in which the temporal dynamics of transcription factors are a key determinant of their capacity to control epigenomic reprogramming, thus enabling the formation of stimulus-specific memory in innate immune sentinel cells.

molecular biology↗

bioRxiv2019

scCAT-seq：single-cell identification and quantification of mRNA isoforms by cost-effective short-read sequencing of cap and tail

The differences in transcription start sites (TSS) and transcription end sites (TES) among gene isoforms can affect the stability, localization, and translation efficiency of mRNA. Isoforms also allow a single gene different functions across various tissues and cells However, methods for efficient genome-wide identification and quantification of RNA isoforms in single cells are still lacking. Here, we introduce single cell Cap And Tail sequencing (scCAT-seq). In conjunction with a novel machine learning algorithm developed for TSS/TES characterization, scCAT-seq can demarcate transcript boundaries of RNA transcripts, providing an unprecedented way to identify and quantify single-cell full-length RNA isoforms based on short-read sequencing. Compared with existing long-read sequencing methods, scCAT-seq has higher efficiency with lower cost. Using scCAT-seq, we identified hundreds of previously uncharacterized full-length transcripts and thousands of alternative transcripts for known genes, quantitatively revealed cell-type specific isoforms with alternative TSSs/TESs in dorsal root ganglion (DRG) neurons, mature oocytes and ageing oocytes, and generated the first atlas of the non-human primate cornea. The approach described here can be widely adapted to other short-read or long-read methods to improve accuracy and efficiency in assessing RNA isoform dynamics among single cells.

genomics↗